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  • Committer: Bazaar Package Importer
  • Author(s): Thomas Weber
  • Date: 2008-08-12 22:28:01 UTC
  • mfrom: (1.1.1 upstream)
  • Revision ID: james.westby@ubuntu.com-20080812222801-b3myaxymt2k5m709
Tags: 1:3.0.1-6lenny1
Allow libhdf5-openmpi-dev to satisfy Octave's hdf5 dependency (closes:
#494139)

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doc/interpreter/HTML/Descriptive-Statistics.html
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   <p><a name="doc_002dmean"></a>
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<div class="defun">
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&mdash; Function File:  <b>mean</b> (<var>x, dim, opt</var>)<var><a name="index-mean-1378"></a></var><br>
 
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&mdash; Function File:  <b>mean</b> (<var>x, dim, opt</var>)<var><a name="index-mean-1377"></a></var><br>
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<blockquote><p>If <var>x</var> is a vector, compute the mean of the elements of <var>x</var>
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     <pre class="example">          mean (x) = SUM_i x(i) / N
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   <p><a name="doc_002dmedian"></a>
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<div class="defun">
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&mdash; Function File:  <b>median</b> (<var>x, dim</var>)<var><a name="index-median-1379"></a></var><br>
 
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&mdash; Function File:  <b>median</b> (<var>x, dim</var>)<var><a name="index-median-1378"></a></var><br>
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<blockquote><p>If <var>x</var> is a vector, compute the median value of the elements of
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<var>x</var>. If the elements of <var>x</var> are sorted, the median is defined
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as
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   <p><a name="doc_002dmeansq"></a>
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<div class="defun">
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&mdash; Function File:  <b>meansq</b> (<var>x</var>)<var><a name="index-meansq-1380"></a></var><br>
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&mdash; Function File:  <b>meansq</b> (<var>x, dim</var>)<var><a name="index-meansq-1381"></a></var><br>
 
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&mdash; Function File:  <b>meansq</b> (<var>x</var>)<var><a name="index-meansq-1379"></a></var><br>
 
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&mdash; Function File:  <b>meansq</b> (<var>x, dim</var>)<var><a name="index-meansq-1380"></a></var><br>
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<blockquote><p>For vector arguments, return the mean square of the values. 
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For matrix arguments, return a row vector containing the mean square
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of each column. With the optional <var>dim</var> argument, returns the
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   <p><a name="doc_002dstd"></a>
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<div class="defun">
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&mdash; Function File:  <b>std</b> (<var>x</var>)<var><a name="index-std-1382"></a></var><br>
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&mdash; Function File:  <b>std</b> (<var>x, opt</var>)<var><a name="index-std-1383"></a></var><br>
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&mdash; Function File:  <b>std</b> (<var>x, opt, dim</var>)<var><a name="index-std-1384"></a></var><br>
 
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&mdash; Function File:  <b>std</b> (<var>x</var>)<var><a name="index-std-1381"></a></var><br>
 
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&mdash; Function File:  <b>std</b> (<var>x, opt</var>)<var><a name="index-std-1382"></a></var><br>
 
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&mdash; Function File:  <b>std</b> (<var>x, opt, dim</var>)<var><a name="index-std-1383"></a></var><br>
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<blockquote><p>If <var>x</var> is a vector, compute the standard deviation of the elements
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of <var>x</var>.
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   <p><a name="doc_002dvar"></a>
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<div class="defun">
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&mdash; Function File:  <b>var</b> (<var>x</var>)<var><a name="index-var-1385"></a></var><br>
 
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&mdash; Function File:  <b>var</b> (<var>x</var>)<var><a name="index-var-1384"></a></var><br>
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<blockquote><p>For vector arguments, return the (real) variance of the values. 
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For matrix arguments, return a row vector containing the variance for
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each column.
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   <p><a name="doc_002dmode"></a>
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<div class="defun">
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&mdash; Function File: [<var>m</var>, <var>f</var>, <var>c</var>] = <b>mode</b> (<var>x, dim</var>)<var><a name="index-mode-1386"></a></var><br>
 
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&mdash; Function File: [<var>m</var>, <var>f</var>, <var>c</var>] = <b>mode</b> (<var>x, dim</var>)<var><a name="index-mode-1385"></a></var><br>
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<blockquote><p>Count the most frequently appearing value. <code>mode</code> counts the
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frequency along the first non-singleton dimension and if two or more
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values have te same frequency returns the smallest of the two in
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   <p><a name="doc_002dcov"></a>
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<div class="defun">
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&mdash; Function File:  <b>cov</b> (<var>x, y</var>)<var><a name="index-cov-1387"></a></var><br>
 
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&mdash; Function File:  <b>cov</b> (<var>x, y</var>)<var><a name="index-cov-1386"></a></var><br>
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<blockquote><p>Compute covariance.
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        <p>If each row of <var>x</var> and <var>y</var> is an observation and each column is
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   <p><a name="doc_002dcor"></a>
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<div class="defun">
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&mdash; Function File:  <b>cor</b> (<var>x, y</var>)<var><a name="index-cor-1388"></a></var><br>
 
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&mdash; Function File:  <b>cor</b> (<var>x, y</var>)<var><a name="index-cor-1387"></a></var><br>
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<blockquote><p>Compute correlation.
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        <p>The (<var>i</var>, <var>j</var>)-th entry of <code>cor (</code><var>x</var><code>, </code><var>y</var><code>)</code> is
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   <p><a name="doc_002dcorrcoef"></a>
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<div class="defun">
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&mdash; Function File:  <b>corrcoef</b> (<var>x, y</var>)<var><a name="index-corrcoef-1389"></a></var><br>
 
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&mdash; Function File:  <b>corrcoef</b> (<var>x, y</var>)<var><a name="index-corrcoef-1388"></a></var><br>
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<blockquote><p>Compute correlation.
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        <p>If each row of <var>x</var> and <var>y</var> is an observation and each column is
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   <p><a name="doc_002dkurtosis"></a>
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<div class="defun">
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&mdash; Function File:  <b>kurtosis</b> (<var>x, dim</var>)<var><a name="index-kurtosis-1390"></a></var><br>
 
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&mdash; Function File:  <b>kurtosis</b> (<var>x, dim</var>)<var><a name="index-kurtosis-1389"></a></var><br>
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<blockquote><p>If <var>x</var> is a vector of length N, return the kurtosis
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     <pre class="example">          kurtosis (x) = N^(-1) std(x)^(-4) sum ((x - mean(x)).^4) - 3
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   <p><a name="doc_002dskewness"></a>
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<div class="defun">
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&mdash; Function File:  <b>skewness</b> (<var>x, dim</var>)<var><a name="index-skewness-1391"></a></var><br>
 
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&mdash; Function File:  <b>skewness</b> (<var>x, dim</var>)<var><a name="index-skewness-1390"></a></var><br>
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<blockquote><p>If <var>x</var> is a vector of length n, return the skewness
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     <pre class="example">          skewness (x) = N^(-1) std(x)^(-3) sum ((x - mean(x)).^3)
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   <p><a name="doc_002dstatistics"></a>
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<div class="defun">
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&mdash; Function File:  <b>statistics</b> (<var>x</var>)<var><a name="index-statistics-1392"></a></var><br>
 
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&mdash; Function File:  <b>statistics</b> (<var>x</var>)<var><a name="index-statistics-1391"></a></var><br>
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<blockquote><p>If <var>x</var> is a matrix, return a matrix with the minimum, first
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quartile, median, third quartile, maximum, mean, standard deviation,
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skewness and kurtosis of the columns of <var>x</var> as its rows.
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   <p><a name="doc_002dmoment"></a>
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<div class="defun">
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&mdash; Function File:  <b>moment</b> (<var>x, p, opt, dim</var>)<var><a name="index-moment-1393"></a></var><br>
 
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&mdash; Function File:  <b>moment</b> (<var>x, p, opt, dim</var>)<var><a name="index-moment-1392"></a></var><br>
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<blockquote><p>If <var>x</var> is a vector, compute the <var>p</var>-th moment of <var>x</var>.
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        <p>If <var>x</var> is a matrix, return the row vector containing the